Search results for: climatological weather data measurement
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26400

Search results for: climatological weather data measurement

25770 Air Quality Analysis Using Machine Learning Models Under Python Environment

Authors: Salahaeddine Sbai

Abstract:

Air quality analysis using machine learning models is a method employed to assess and predict air pollution levels. This approach leverages the capabilities of machine learning algorithms to analyze vast amounts of air quality data and extract valuable insights. By training these models on historical air quality data, they can learn patterns and relationships between various factors such as weather conditions, pollutant emissions, and geographical features. The trained models can then be used to predict air quality levels in real-time or forecast future pollution levels. This application of machine learning in air quality analysis enables policymakers, environmental agencies, and the general public to make informed decisions regarding health, environmental impact, and mitigation strategies. By understanding the factors influencing air quality, interventions can be implemented to reduce pollution levels, mitigate health risks, and enhance overall air quality management. Climate change is having significant impacts on Morocco, affecting various aspects of the country's environment, economy, and society. In this study, we use some machine learning models under python environment to predict and analysis air quality change over North of Morocco to evaluate the climate change impact on agriculture.

Keywords: air quality, machine learning models, pollution, pollutant emissions

Procedia PDF Downloads 62
25769 The Bone Remodeling of Mandible in Bruxers

Authors: Eni Rahmi, Rasmi Rikmasari, Taufik Soemarsongko

Abstract:

Background: One of the bad habits that requires a treatment and viewed as a risk factor of the temporomandibular disorder is bruxism. Bruxism defined as an awake and/or asleep parafunctional activities include grinding, gnashing, bracing or clenching of the teeth. In particular circumstances such as an increased frequency of episode, duration and the intensity of masseter contractions, caused phenomenon with pathological consequences, i.e., mandibular remodeling. The remodeling in mandibular angle was associated with the masseter and pterygoid medial muscles attachment which in its insertion area. The aim of this study was to compare the mandibular remodeling between bruxers and non-bruxers with ramus height, gonial angle and bigonial width as parameters, and to identify correlation among those parameters in bruxers, using panoramic radiographic. Methods: This study was conducted on 35 bruxers (10 phasic bruxism patients, 6 tonic bruxism patients, and 19 mixed bruxism patients) and 20 non-bruxers as control group. The data were obtained by using questionary, clinical examination, and radiographic measurement. Panoramic radiograph measurement was done using soft CBCT EPX Impla (E-Woo Korea). The data was analyzed by using Paired T-Test to see differences between parameters in both group and Pearson Correlation Test to evaluate correlation among parameters. Result: There was significant differences between bruxers and non-bruxers in ramus heights (p=0,04), bigonial widths (p=0,001), and gonial angles(p=0,015). The bruxers showed increased ramus heights and bigonial widths, in other hand, the gonial angles decreased. This study also found that there was highly correlation among ramus height, gonial angles, and bigonial widths. Conclusion: the bone remodeling occurred on inferior and posterior border of mandibular angle in bruxism patient, indicated by the form and size differences between bruxers (phasic bruxism, tonic bruxism, and mixed bruxism) with non-bruxers, which shown by panoramic radiograph.

Keywords: bruxism, ramus height, gonial angle, bigonial width

Procedia PDF Downloads 272
25768 Influence of Environmental Temperature on Dairy Herd Performance and Behaviour

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, S. Harapanahalli, J. Walsh

Abstract:

The objective of this study was to determine the effects of environmental stressors on the performance of lactating dairy cows and discuss some future trends. There exists a relationship between the meteorological data and milk yield prediction accuracy in pasture-based dairy systems. New precision technologies are available and are being developed to improve the sustainability of the dairy industry. Some of these technologies focus on welfare of individual animals on dairy farms. These technologies allow the automatic identification of animal behaviour and health events, greatly increasing overall herd health and yield while reducing animal health inspection demands and long-term animal healthcare costs. The data set consisted of records from 489 dairy cows at two dairy farms and temperature measured from the nearest meteorological weather station in 2018. The effects of temperature on milk production and behaviour of animals were analyzed. The statistical results indicate different effects of temperature on milk yield and behaviour. The “comfort zone” for animals is in the range 10 °C to 20 °C. Dairy cows out of this zone had to decrease or increase their metabolic heat production, and it affected their milk production and behaviour.

Keywords: behavior, milk yield, temperature, precision technologies

Procedia PDF Downloads 87
25767 Physicochemical Characterization of Coastal Aerosols over the Mediterranean Comparison with Weather Research and Forecasting-Chem Simulations

Authors: Stephane Laussac, Jacques Piazzola, Gilles Tedeschi

Abstract:

Estimation of the impact of atmospheric aerosols on the climate evolution is an important scientific challenge. One of a major source of particles is constituted by the oceans through the generation of sea-spray aerosols. In coastal areas, marine aerosols can affect air quality through their ability to interact chemically and physically with other aerosol species and gases. The integration of accurate sea-spray emission terms in modeling studies is then required. However, it was found that sea-spray concentrations are not represented with the necessary accuracy in some situations, more particularly at short fetch. In this study, the WRF-Chem model was implemented on a North-Western Mediterranean coastal region. WRF-Chem is the Weather Research and Forecasting (WRF) model online-coupled with chemistry for investigation of regional-scale air quality which simulates the emission, transport, mixing, and chemical transformation of trace gases and aerosols simultaneously with the meteorology. One of the objectives was to test the ability of the WRF-Chem model to represent the fine details of the coastal geography to provide accurate predictions of sea spray evolution for different fetches and the anthropogenic aerosols. To assess the performance of the model, a comparison between the model predictions using a local emission inventory and the physicochemical analysis of aerosol concentrations measured for different wind direction on the island of Porquerolles located 10 km south of the French Riviera is proposed.

Keywords: sea-spray aerosols, coastal areas, sea-spray concentrations, short fetch, WRF-Chem model

Procedia PDF Downloads 172
25766 Microwave Dielectric Constant Measurements of Titanium Dioxide Using Five Mixture Equations

Authors: Jyh Sheen, Yong-Lin Wang

Abstract:

This research dedicates to find a different measurement procedure of microwave dielectric properties of ceramic materials with high dielectric constants. For the composite of ceramic dispersed in the polymer matrix, the dielectric constants of the composites with different concentrations can be obtained by various mixture equations. The other development of mixture rule is to calculate the permittivity of ceramic from measurements on composite. To do this, the analysis method and theoretical accuracy on six basic mixture laws derived from three basic particle shapes of ceramic fillers have been reported for dielectric constants of ceramic less than 40 at microwave frequency. Similar researches have been done for other well-known mixture rules. They have shown that both the physical curve matching with experimental results and low potential theory error are important to promote the calculation accuracy. Recently, a modified of mixture equation for high dielectric constant ceramics at microwave frequency has also been presented for strontium titanate (SrTiO3) which was selected from five more well known mixing rules and has shown a good accuracy for high dielectric constant measurements. However, it is still not clear the accuracy of this modified equation for other high dielectric constant materials. Therefore, the five more well known mixing rules are selected again to understand their application to other high dielectric constant ceramics. The other high dielectric constant ceramic, TiO2 with dielectric constant 100, was then chosen for this research. Their theoretical error equations are derived. In addition to the theoretical research, experimental measurements are always required. Titanium dioxide is an interesting ceramic for microwave applications. In this research, its powder is adopted as the filler material and polyethylene powder is like the matrix material. The dielectric constants of those ceramic-polyethylene composites with various compositions were measured at 10 GHz. The theoretical curves of the five published mixture equations are shown together with the measured results to understand the curve matching condition of each rule. Finally, based on the experimental observation and theoretical analysis, one of the five rules was selected and modified to a new powder mixture equation. This modified rule has show very good curve matching with the measurement data and low theoretical error. We can then calculate the dielectric constant of pure filler medium (titanium dioxide) by those mixing equations from the measured dielectric constants of composites. The accuracy on the estimating dielectric constant of pure ceramic by various mixture rules will be compared. This modified mixture rule has also shown good measurement accuracy on the dielectric constant of titanium dioxide ceramic. This study can be applied to the microwave dielectric properties measurements of other high dielectric constant ceramic materials in the future.

Keywords: microwave measurement, dielectric constant, mixture rules, composites

Procedia PDF Downloads 343
25765 A Convolution Neural Network Approach to Predict Pes-Planus Using Plantar Pressure Mapping Images

Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

Abstract:

Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

Procedia PDF Downloads 335
25764 A Review on Trends in Measurement of Port Performance

Authors: J. Racedo, J. Torres

Abstract:

Globalization has led to a worldwide competition for participation in markets of goods and productive factors, with significant effects on transports requirements. The port industry has not been an exception to this event, in fact, it has received increasing attention in recent years due to its crucial role on international trade. Because of this, the measurement of port performance has become an important issue in transport policy. Port performance and port efficiency has been widely studied in the last decades, resulting in noteworthy contributions to improving the industry competitiveness. In this paper, we aim to present a review of the literature on port performance and the relation between this concept and transport policies. This study has the objective to describe the approaches that have been developed in recent years, and especially those that include the modeling of public policies. Finally, we highlight existing gaps in this field, as well as possible directions for future research.

Keywords: port performance, port efficiency, transport, policy

Procedia PDF Downloads 309
25763 Effect of Traffic Volume and Its Composition on Vehicular Speed under Mixed Traffic Conditions: A Kriging Based Approach

Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

Abstract:

Use of speed prediction models sometimes appears as a feasible alternative to laborious field measurement particularly, in case when field data cannot fulfill designer’s requirements. However, developing speed models is a challenging task specifically in the context of developing countries like India where vehicles with diverse static and dynamic characteristics use the same right of way without any segregation. Here the traffic composition plays a significant role in determining the vehicular speed. The present research was carried out to examine the effects of traffic volume and its composition on vehicular speed under mixed traffic conditions. Classified traffic volume and speed data were collected from different geometrically identical six lane divided arterials in New Delhi. Based on these field data, speed prediction models were developed for individual vehicle category adopting Kriging approximation technique, an alternative for commonly used regression. These models are validated with the data set kept aside earlier for validation purpose. The predicted speeds showed a great deal of agreement with the observed values and also the model outperforms all other existing speed models. Finally, the proposed models were utilized to evaluate the effect of traffic volume and its composition on speed.

Keywords: speed, Kriging, arterial, traffic volume

Procedia PDF Downloads 335
25762 Optimal Evaluation of Weather Risk Insurance for Wheat

Authors: Slim Amami

Abstract:

A model is developed to prevent the risks related to climate conditions in the agricultural sector. It will determine the yearly optimum premium to be paid by a farmer in order to reach his required turnover. The model is mainly based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, main ones of which are daily average sunlight, rainfall and temperature. By a simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is deduced from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. Optimal premium is then deduced, and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect their harvest. The application to wheat production in the French Oise department illustrates the reliability of the present model with as low as 6% difference between predicted and real data. The model can be adapted to almost every agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, database, meteorological factors, production model, optimal price

Procedia PDF Downloads 200
25761 Tank Barrel Surface Damage Detection Algorithm

Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

Abstract:

The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

Procedia PDF Downloads 124
25760 Improvement of Piezoresistive Pressure Sensor Accuracy by Means of Current Loop Circuit Using Optimal Digital Signal Processing

Authors: Peter A. L’vov, Roman S. Konovalov, Alexey A. L’vov

Abstract:

The paper presents the advanced digital modification of the conventional current loop circuit for pressure piezoelectric transducers. The optimal DSP algorithms of current loop responses by the maximum likelihood method are applied for diminishing of measurement errors. The loop circuit has some additional advantages such as the possibility to operate with any type of resistance or reactance sensors, and a considerable increase in accuracy and quality of measurements to be compared with AC bridges. The results obtained are dedicated to replace high-accuracy and expensive measuring bridges with current loop circuits.

Keywords: current loop, maximum likelihood method, optimal digital signal processing, precise pressure measurement

Procedia PDF Downloads 507
25759 Empirical Analysis of Velocity Behavior for Collaborative Robots in Transient Contact Cases

Authors: C. Schneider, M. M. Seizmeir, T. Suchanek, M. Hutter-Mironovova, M. Bdiwi, M. Putz

Abstract:

In this paper, a suitable measurement setup is presented to conduct force and pressure measurements for transient contact cases at the example of lathe machine tending. Empirical measurements were executed on a selected collaborative robot’s behavior regarding allowable operating speeds under consideration of sensor- and workpiece-specific factors. Comparisons between the theoretic calculations proposed in ISO/TS 15066 and the practical measurement results reveal a basis for future research. With the created database, preliminary risk assessment and economic assessment procedures of collaborative machine tending cells can be facilitated.

Keywords: biomechanical thresholds, collaborative robots, force and pressure measurements, machine tending, transient contact

Procedia PDF Downloads 212
25758 Application of Neutron-Gamma Technologies for Soil Elemental Content Determination and Mapping

Authors: G. Yakubova, A. Kavetskiy, S. A. Prior, H. A. Torbert

Abstract:

In-situ soil carbon determination over large soil surface areas (several hectares) is required in regard to carbon sequestration and carbon credit issues. This capability is important for optimizing modern agricultural practices and enhancing soil science knowledge. Collecting and processing representative field soil cores for traditional laboratory chemical analysis is labor-intensive and time-consuming. The neutron-stimulated gamma analysis method can be used for in-situ measurements of primary elements in agricultural soils (e.g., Si, Al, O, C, Fe, and H). This non-destructive method can assess several elements in large soil volumes with no need for sample preparation. Neutron-gamma soil elemental analysis utilizes gamma rays issued from different neutron-nuclei interactions. This process has become possible due to the availability of commercial portable pulse neutron generators, high-efficiency gamma detectors, reliable electronics, and measurement/data processing software complimented by advances in state-of-the-art nuclear physics methods. In Pulsed Fast Thermal Neutron Analysis (PFTNA), soil irradiation is accomplished using a pulsed neutron flux, and gamma spectra acquisition occurs both during and between pulses. This method allows the inelastic neutron scattering (INS) gamma spectrum to be separated from the thermal neutron capture (TNC) spectrum. Based on PFTNA, a mobile system for field-scale soil elemental determinations (primarily carbon) was developed and constructed. Our scanning methodology acquires data that can be directly used for creating soil elemental distribution maps (based on ArcGIS software) in a reasonable timeframe (~20-30 hectares per working day). Created maps are suitable for both agricultural purposes and carbon sequestration estimates. The measurement system design, spectra acquisition process, strategy for acquiring field-scale carbon content data, and mapping of agricultural fields will be discussed.

Keywords: neutron gamma analysis, soil elemental content, carbon sequestration, carbon credit, soil gamma spectroscopy, portable neutron generators, ArcMap mapping

Procedia PDF Downloads 72
25757 A Web Service Based Sensor Data Management System

Authors: Rose A. Yemson, Ping Jiang, Oyedeji L. Inumoh

Abstract:

The deployment of wireless sensor network has rapidly increased, however with the increased capacity and diversity of sensors, and applications ranging from biological, environmental, military etc. generates tremendous volume of data’s where more attention is placed on the distributed sensing and little on how to manage, analyze, retrieve and understand the data generated. This makes it more quite difficult to process live sensor data, run concurrent control and update because sensor data are either heavyweight, complex, and slow. This work will focus on developing a web service platform for automatic detection of sensors, acquisition of sensor data, storage of sensor data into a database, processing of sensor data using reconfigurable software components. This work will also create a web service based sensor data management system to monitor physical movement of an individual wearing wireless network sensor technology (SunSPOT). The sensor will detect movement of that individual by sensing the acceleration in the direction of X, Y and Z axes accordingly and then send the sensed reading to a database that will be interfaced with an internet platform. The collected sensed data will determine the posture of the person such as standing, sitting and lying down. The system is designed using the Unified Modeling Language (UML) and implemented using Java, JavaScript, html and MySQL. This system allows real time monitoring an individual closely and obtain their physical activity details without been physically presence for in-situ measurement which enables you to work remotely instead of the time consuming check of an individual. These details can help in evaluating an individual’s physical activity and generate feedback on medication. It can also help in keeping track of any mandatory physical activities required to be done by the individuals. These evaluations and feedback can help in maintaining a better health status of the individual and providing improved health care.

Keywords: HTML, java, javascript, MySQL, sunspot, UML, web-based, wireless network sensor

Procedia PDF Downloads 196
25756 Neural Network Monitoring Strategy of Cutting Tool Wear of Horizontal High Speed Milling

Authors: Kious Mecheri, Hadjadj Abdechafik, Ameur Aissa

Abstract:

The wear of cutting tool degrades the quality of the product in the manufacturing processes. The online monitoring of the cutting tool wear level is very necessary to prevent the deterioration of the quality of machining. Unfortunately there is not a direct manner to measure the cutting tool wear online. Consequently we must adopt an indirect method where wear will be estimated from the measurement of one or more physical parameters appearing during the machining process such as the cutting force, the vibrations, or the acoustic emission etc. In this work, a neural network system is elaborated in order to estimate the flank wear from the cutting force measurement and the cutting conditions.

Keywords: flank wear, cutting forces, high speed milling, signal processing, neural network

Procedia PDF Downloads 371
25755 The Benefits of Security Culture for Improving Physical Protection Systems at Detection and Radiation Measurement Laboratory

Authors: Ari S. Prabowo, Nia Febriyanti, Haryono B. Santosa

Abstract:

Security function that is called as Physical Protection Systems (PPS) has functions to detect, delay and response. Physical Protection Systems (PPS) in Detection and Radiation Measurement Laboratory needs to be improved continually by using internal resources. The nuclear security culture provides some potentials to support this research. The study starts by identifying the security function’s weaknesses and its strengths of security culture as a purpose. Secondly, the strengths of security culture are implemented in the laboratory management. Finally, a simulation was done to measure its effectiveness. Some changes were happened in laboratory personnel behaviors and procedures. All became more prudent. The results showed a good influence of nuclear security culture in laboratory security functions.

Keywords: laboratory, physical protection system, security culture, security function

Procedia PDF Downloads 161
25754 Genre Analysis of Postgraduate Theses and Dissertations: Case of Statement of the Problem

Authors: H. Mashhady, H. A. Manzoori, M. Doosti, M. Fatollahi

Abstract:

This study reports a descriptive research in the form of a genre analysis of postgraduates' theses and dissertations at three Iranian universities, including Ferdowsi, Tehran, and Tarbiat Moddares universities. The researchers sought to depict the generic structure of “statement of the problem” section of PhD dissertations and MA theses. Moreover, researchers desired to find any probable variety based on the year the dissertations belonged, to see weather genre-consciousness developed among Iranian postgraduates. To obtain data, “statement of the problem” section of 90 Ph.D. dissertations and MA theses from 2001 to 2013 in Teaching English as a Foreign Language (TEFL) at above-mentioned universities was selected. Frequency counts was employed for the quantitative method of data analysis, while genre analysis was used as the qualitative method. Inter-rater reliability was found to be about 0.93. Results revealed that students in different degrees at each of these universities used various generic structures for writing “statement of the problem”. Moreover, comparison of different time periods (2001-2006, and 2007-2013) revealed that postgraduates in the second time period, regardless of their degree and university, employed more similar generic structures which can be optimistically attributed to a general raise in genre awareness.

Keywords: genre, genre analysis, Ph.D. and MA dissertations, statement of the problem, generic structure

Procedia PDF Downloads 647
25753 Measurement of Operational and Environmental Performance of the Coal-Fired Power Plants in India by Using Data Envelopment Analysis

Authors: Vijay Kumar Bajpai, Sudhir Kumar Singh

Abstract:

In this study, the performance analyses of the twenty five coal-fired power plants (CFPPs) used for electricity generation are carried out through various data envelopment analysis (DEA) models. Three efficiency indices are defined and pursued. During the calculation of the operational performance, energy and non-energy variables are used as input, and net electricity produced is used as desired output. CO2 emitted to the environment is used as the undesired output in the computation of the pure environmental performance while in Model-3 CO2 emissions is considered as detrimental input in the calculation of operational and environmental performance. Empirical results show that most of the plants are operating in increasing returns to scale region and Mettur plant is efficient one with regards to energy use and environment. The result also indicates that the undesirable output effect is insignificant in the research sample. The present study will provide clues to plant operators towards raising the operational and environmental performance of CFPPs.

Keywords: coal fired power plants, environmental performance, data envelopment analysis, operational performance

Procedia PDF Downloads 429
25752 Climate Changes Impact on Artificial Wetlands

Authors: Carla Idely Palencia-Aguilar

Abstract:

Artificial wetlands play an important role at Guasca Municipality in Colombia, not only because they are used for the agroindustry, but also because more than 45 species were found, some of which are endemic and migratory birds. Remote sensing was used to determine the changes in the area occupied by water of artificial wetlands by means of Aster and Modis images for different time periods. Evapotranspiration was also determined by three methods: Surface Energy Balance System-Su (SEBS) algorithm, Surface Energy Balance- Bastiaanssen (SEBAL) algorithm, and Potential Evapotranspiration- FAO. Empirical equations were also developed to determine the relationship between Normalized Difference Vegetation Index (NDVI) versus net radiation, ambient temperature and rain with an obtained R2 of 0.83. Groundwater level fluctuations on a daily basis were studied as well. Data from a piezometer placed next to the wetland were fitted with rain changes (with two weather stations located at the proximities of the wetlands) by means of multiple regression and time series analysis, the R2 from the calculated and measured values resulted was higher than 0.98. Information from nearby weather stations provided information for ordinary kriging as well as the results for the Digital Elevation Model (DEM) developed by using PCI software. Standard models (exponential, spherical, circular, gaussian, linear) to describe spatial variation were tested. Ordinary Cokriging between height and rain variables were also tested, to determine if the accuracy of the interpolation would increase. The results showed no significant differences giving the fact that the mean result of the spherical function for the rain samples after ordinary kriging was 58.06 and a standard deviation of 18.06. The cokriging using for the variable rain, a spherical function; for height variable, the power function and for the cross variable (rain and height), the spherical function had a mean of 57.58 and a standard deviation of 18.36. Threatens of eutrophication were also studied, given the unconsciousness of neighbours and government deficiency. Water quality was determined over the years; different parameters were studied to determine the chemical characteristics of water. In addition, 600 pesticides were studied by gas and liquid chromatography. Results showed that coliforms, nitrogen, phosphorous and prochloraz were the most significant contaminants.

Keywords: DEM, evapotranspiration, geostatistics, NDVI

Procedia PDF Downloads 96
25751 The Effect of Mental Workload Towards Mental Fatigue on Customer Care Agent Using Electroencephalogram

Authors: Maya Arlini Puspasari, Shafira Karamina Alifah, Hardianto Iridiastadi

Abstract:

High mental workload can lead to fatigue and further result in decreased concentration and work performance. This study is conducted to see the effects of mental workload towards mental fatigue. Mental fatigue measurement was conducted at the first and the last 10 minutes of the working time using electroencephalogram, while mental workload measurement was conducted after the work is completed using the NASA-TLX questionnaire. The result shows that there is an increase in alpha band which indicates an increase in mental fatigue. This study also shows absolute alpha is more sensitive compared to the relative alpha. This study proves that there is a relationship between mental workload and mental fatigue although not relatively strong.

Keywords: mental workload, electroencephalogram, customer care agents, NASA-TLX

Procedia PDF Downloads 205
25750 Comparison of Data Reduction Algorithms for Image-Based Point Cloud Derived Digital Terrain Models

Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

Abstract:

Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

Procedia PDF Downloads 135
25749 A POX Controller Module to Collect Web Traffic Statistics in SDN Environment

Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

Abstract:

Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Keywords: mininet, OpenFlow, POX controller, SDN

Procedia PDF Downloads 209
25748 Design of a Compact Herriott Cell for Heat Flux Measurement Applications

Authors: R. G. Ramírez-Chavarría, C. Sánchez-Pérez, V. Argueta-Díaz

Abstract:

In this paper we present the design of an optical device based on a Herriott multi-pass cell fabricated on a small sized acrylic slab for heat flux measurements using the deflection of a laser beam propagating inside the cell. The beam deflection is produced by the heat flux conducted to the acrylic slab due to a gradient in the refractive index. The use of a long path cell as the sensitive element in this measurement device, gives the possibility of high sensitivity within a small size device. We present the optical design as well as some experimental results in order to validate the device’s operation principle.

Keywords: heat flux, Herriott cell, optical beam deflection, thermal conductivity

Procedia PDF Downloads 625
25747 Absorbed Dose Measurements for Teletherapy Prediction of Superficial Dose Using Halcyon Linear Accelerator

Authors: Raymond Limen Njinga, Adeneye Samuel Olaolu, Akinyode Ojumoola Ajimo

Abstract:

Introduction: Measurement of entrance dose and dose at different depths is essential to avoid overdose and underdose of patients. The aim of this study is to verify the variation in the absorbed dose using a water-equivalent material. Materials and Methods: The plastic phantom was arranged on the couch of the halcyon linear accelerator by Varian, with the farmer ionization chamber inserted and connected to the electrometer. The image of the setup was taken using the High-Quality Single 1280x1280x16 higher on the service mode to check the alignment with the isocenter. The beam quality TPR₂₀,₁₀ (Tissue phantom ratio) was done to check the beam quality of the machine at a field size of 10 cm x 10 cm. The calibration was done using SAD type set-up at a depth of 5 cm. This process was repeated for ten consecutive weeks, and the values were recorded. Results: The results of the beam output for the teletherapy machine were satisfactory and accepted in comparison with the commissioned measurement of 0.62. The beam quality TPR₂₀,₁₀ (Tissue phantom ratio) was reasonable with respect to the beam quality of the machine at a field size of 10 cm x 10 cm. Conclusion: The results of the beam quality and the absorbed dose rate showed a good consistency over the period of ten weeks with the commissioned measurement value.

Keywords: linear accelerator, absorbed dose rate, isocenter, phantom, ionization chamber

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25746 W-WING: Aeroelastic Demonstrator for Experimental Investigation into Whirl Flutter

Authors: Jiri Cecrdle

Abstract:

This paper describes the concept of the W-WING whirl flutter aeroelastic demonstrator. Whirl flutter is the specific case of flutter that accounts for the additional dynamic and aerodynamic influences of the engine rotating parts. The instability is driven by motion-induced unsteady aerodynamic propeller forces and moments acting in the propeller plane. Whirl flutter instability is a serious problem that may cause the unstable vibration of a propeller mounting, leading to the failure of an engine installation or an entire wing. The complicated physical principle of whirl flutter required the experimental validation of the analytically gained results. W-WING aeroelastic demonstrator has been designed and developed at Czech Aerospace Research Centre (VZLU) Prague, Czechia. The demonstrator represents the wing and engine of the twin turboprop commuter aircraft. Contrary to the most of past demonstrators, it includes a powered motor and thrusting propeller. It allows the changes of the main structural parameters influencing the whirl flutter stability characteristics. Propeller blades are adjustable at standstill. The demonstrator is instrumented by strain gauges, accelerometers, revolution-counting impulse sensor, sensor of airflow velocity, and the thrust measurement unit. Measurement is supported by the in house program providing the data storage and real-time depiction in the time domain as well as pre-processing into the form of the power spectral densities. The engine is linked with a servo-drive unit, which enables maintaining of the propeller revolutions (constant or controlled rate ramp) and monitoring of immediate revolutions and power. Furthermore, the program manages the aerodynamic excitation of the demonstrator by the aileron flapping (constant, sweep, impulse). Finally, it provides the safety guard to prevent any structural failure of the demonstrator hardware. In addition, LMS TestLab system is used for the measurement of the structure response and for the data assessment by means of the FFT- and OMA-based methods. The demonstrator is intended for the experimental investigations in the VZLU 3m-diameter low-speed wind tunnel. The measurement variant of the model is defined by the structural parameters: pitch and yaw attachment stiffness, pitch and yaw hinge stations, balance weight station, propeller type (duralumin or steel blades), and finally, angle of attack of the propeller blade 75% section (). The excitation is provided either by the airflow turbulence or by means of the aerodynamic excitation by the aileron flapping using a frequency harmonic sweep. The experimental results are planned to be utilized for validation of analytical methods and software tools in the frame of development of the new complex multi-blade twin-rotor propulsion system for the new generation regional aircraft. Experimental campaigns will include measurements of aerodynamic derivatives and measurements of stability boundaries for various configurations of the demonstrator.

Keywords: aeroelasticity, flutter, whirl flutter, W WING demonstrator

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25745 Spatial Cognition and 3-Dimensional Vertical Urban Design Guidelines

Authors: Hee Sun (Sunny) Choi, Gerhard Bruyns, Wang Zhang, Sky Cheng, Saijal Sharma

Abstract:

The main focus of this paper is to propose a comprehensive framework for the cognitive measurement and modelling of the built environment. This will involve exploring and measuring neural mechanisms. The aim is to create a foundation for further studies in this field that are consistent and rigorous. Additionally, this framework will facilitate collaboration with cognitive neuroscientists by establishing a shared conceptual basis. The goal of this research is to develop a human-centric approach for urban design that is scientific and measurable, producing a set of urban design guidelines that incorporate cognitive measurement and modelling. By doing so, the broader intention is to design urban spaces that prioritize human needs and well-being, making them more liveable.

Keywords: vertical urbanism, human centric design, spatial cognition and psychology, vertical urban design guidelines

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25744 An Intelligent Prediction Method for Annular Pressure Driven by Mechanism and Data

Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li, Shuo Zhu, Shiming Duan, Xuezhe Yao

Abstract:

Accurate calculation of wellbore pressure is of great significance to prevent wellbore risk during drilling. The traditional mechanism model needs a lot of iterative solving procedures in the calculation process, which reduces the calculation efficiency and is difficult to meet the demand of dynamic control of wellbore pressure. In recent years, many scholars have introduced artificial intelligence algorithms into wellbore pressure calculation, which significantly improves the calculation efficiency and accuracy of wellbore pressure. However, due to the ‘black box’ property of intelligent algorithm, the existing intelligent calculation model of wellbore pressure is difficult to play a role outside the scope of training data and overreacts to data noise, often resulting in abnormal calculation results. In this study, the multi-phase flow mechanism is embedded into the objective function of the neural network model as a constraint condition, and an intelligent prediction model of wellbore pressure under the constraint condition is established based on more than 400,000 sets of pressure measurement while drilling (MPD) data. The constraint of the multi-phase flow mechanism makes the prediction results of the neural network model more consistent with the distribution law of wellbore pressure, which overcomes the black-box attribute of the neural network model to some extent. The main performance is that the accuracy of the independent test data set is further improved, and the abnormal calculation values basically disappear. This method is a prediction method driven by MPD data and multi-phase flow mechanism, and it is the main way to predict wellbore pressure accurately and efficiently in the future.

Keywords: multiphase flow mechanism, pressure while drilling data, wellbore pressure, mechanism constraints, combined drive

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25743 Analysis of Big Data

Authors: Sandeep Sharma, Sarabjit Singh

Abstract:

As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

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25742 Indicator-Based Approach for Assessing Socio Economic Vulnerability of Dairy Farmers to Impacts of Climate Variability and Change in India

Authors: Aparna Radhakrishnan, Jancy Gupta, R. Dileepkumar

Abstract:

This paper aims at assessing the Socio Economic Vulnerability (SEV) of dairy farmers to Climate Variability and Change (CVC) in 3 states of Western Ghat region in India. For this purpose, a composite SEV index has been developed on the basis of functional relationships amongst sensitivity, exposure and adaptive capacity using 30 indicators related to dairy farming underlying the principles of Intergovernmental Panel on Climate Change and Fussel framework for nomenclature of vulnerable situation. Household level data were collected through Participatory Rural Appraisal and personal interviews of 540 dairy farmers of nine taluks, three each from a district selected from Kerala, Karnataka and Maharashtra, complemented by thirty years of gridded weather data. The data were normalized and then combined into three indices for sensitivity, exposure and adaptive capacity, which were then averaged with weights given using principal component analysis, to obtain the overall SEV index. Results indicated that the taluks of Western Ghats are vulnerable to CVC. The dairy farmers of Pulpally taluka were most vulnerable having the SEV score +1.24 and 42.66% farmers under high-level vulnerability category. Even though the taluks are geographically closer, there is wide variation in SEV components. Policies for incentivizing the ‘climate risk adaptation’ costs for small and marginal farmers and livelihood infrastructure for mitigating risks and promoting grass root level innovations are necessary to sustain dairy farming of the region.

Keywords: climate change, dairy, vulnerability, livelihoods, adaptation strategies

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25741 Chaotic Analysis of Acid Rains with Times Series of pH Degree, Nitrate and Sulphate Concentration on Wet Samples

Authors: Aysegul Sener, Gonca Tuncel Memis, Mirac Kamislioglu

Abstract:

Chaos theory is one of the new paradigms of science since the last century. After determining chaos in the weather systems by Edward Lorenz the popularity of the theory was increased. Chaos is observed in many natural systems and studies continue to defect chaos to other natural systems. Acid rain is one of the environmental problems that have negative effects on environment and acid rains values are monitored continuously. In this study, we aim that analyze the chaotic behavior of acid rains in Turkey with the chaotic defecting approaches. The data of pH degree of rain waters, concentration of sulfate and nitrate data of wet rain water samples in the rain collecting stations which are located in different regions of Turkey are provided by Turkish State Meteorology Service. Lyapunov exponents, reconstruction of the phase space, power spectrums are used in this study to determine and predict the chaotic behaviors of acid rains. As a result of the analysis it is found that acid rain time series have positive Lyapunov exponents and wide power spectrums and chaotic behavior is observed in the acid rain time series.

Keywords: acid rains, chaos, chaotic analysis, Lypapunov exponents

Procedia PDF Downloads 124